src/core/CL/kernels/CLSpaceToBatchLayerKernel.cpp - platform/external/ComputeLibrary - Git at Google

 /*
  * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
  * Permission is hereby granted, free of charge, to any person obtaining a copy
  * of this software and associated documentation files (the "Software"), to
  * deal in the Software without restriction, including without limitation the
  * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
  * sell copies of the Software, and to permit persons to whom the Software is
  * furnished to do so, subject to the following conditions:
  *
  * The above copyright notice and this permission notice shall be included in all
  * copies or substantial portions of the Software.
  *
  * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
 #include "arm_compute/core/CL/kernels/CLSpaceToBatchLayerKernel.h"

 #include "arm_compute/core/CL/CLHelpers.h"
 #include "arm_compute/core/CL/CLValidate.h"
 #include "arm_compute/core/CL/ICLTensor.h"
 #include "arm_compute/core/utils/misc/ShapeCalculator.h"

 using namespace arm_compute::misc::shape_calculator;

 namespace arm_compute
 {
 namespace
 {
 Status validate_arguments(const ITensorInfo *input, const ITensorInfo *block_info, const ITensorInfo *padddings, const ITensorInfo *output)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, block_info, padddings, output);
     ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(block_info, 1, DataType::S32);
     ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);
     ARM_COMPUTE_RETURN_ERROR_ON(block_info->num_dimensions() > 1);
     ARM_COMPUTE_RETURN_ERROR_ON(padddings->num_dimensions() > 2);
     ARM_COMPUTE_RETURN_ERROR_ON(padddings->tensor_shape()[1] != block_info->tensor_shape()[0]);

     // Validate output if initialized
     if(output->total_size() != 0)
     {
         const DataLayout data_layout = input->data_layout();
         const int        idx_channel = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
         ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_channel] != output->tensor_shape()[idx_channel]);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
     }

     return Status{};
 }
 Status validate_arguments_static(const ITensorInfo *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right,
                                  const ITensorInfo *output)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_RETURN_ERROR_ON(block_shape_x < 1 || block_shape_y < 1);
     ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);

     // Validate output if initialized
     if(output->total_size() != 0)
     {
         const DataLayout data_layout = input->data_layout();
         const int        idx_width   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
         const int        idx_height  = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
         const int        idx_channel = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
         const int        idx_batch   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);
         ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_width] < padding_left.x() + padding_right.y());
         ARM_COMPUTE_RETURN_ERROR_ON((input->tensor_shape()[idx_width] + padding_left.x() + padding_right.x()) % block_shape_x != 0);
         ARM_COMPUTE_RETURN_ERROR_ON((input->tensor_shape()[idx_height] + padding_left.y() + padding_right.y()) % block_shape_y != 0);
         ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_channel] != output->tensor_shape()[idx_channel]);
         ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_batch] % (block_shape_x * block_shape_y) != 0);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
     }

     return Status{};
 }
 } // namespace

 CLSpaceToBatchLayerKernel::CLSpaceToBatchLayerKernel()
     : _input(nullptr), _block_shape(nullptr), _paddings(nullptr), _output(nullptr)
 {
 }

 void CLSpaceToBatchLayerKernel::configure(const ICLTensor *input, const ICLTensor *block_shape, const ICLTensor *paddings, ICLTensor *output)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), block_shape->info(), paddings->info(), output->info()));

     _input       = input;
     _block_shape = block_shape;
     _paddings    = paddings;
     _output      = output;

     const DataLayout data_layout = input->info()->data_layout();
     const int        idx_width   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
     const int        idx_height  = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
     const int        idx_batch   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);

     // Create kernel
     CLBuildOptions build_opts;
     build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
     build_opts.add_option("-DWIDTH_OUT=" + support::cpp11::to_string(output->info()->dimension(idx_width)));
     build_opts.add_option("-DHEIGHT_OUT=" + support::cpp11::to_string(output->info()->dimension(idx_height)));
     build_opts.add_option("-DBATCH_SIZE=" + support::cpp11::to_string(output->info()->dimension(idx_batch)));
     build_opts.add_option("-DWIDTH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_width)));
     build_opts.add_option("-DHEIGHT_IN=" + support::cpp11::to_string(input->info()->dimension(idx_height)));
     build_opts.add_option("-DBATCH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_batch)));
     _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("space_to_batch_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options()));

     // Configure kernel window
     Window win = calculate_max_window(*output->info(), Steps());
     ICLKernel::configure_internal(win);
 }

 void CLSpaceToBatchLayerKernel::configure(const ICLTensor *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right,
                                           ICLTensor *output)
 {
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);

     TensorShape output_shape = misc::shape_calculator::compute_space_to_batch_shape(input->info(), block_shape_x, block_shape_y, padding_left, padding_right);
     auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->quantization_info());

     ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_static(input->info(), block_shape_x, block_shape_y, padding_left, padding_right, output->info()));

     _input  = input;
     _output = output;

     const DataLayout data_layout = input->info()->data_layout();
     const int        idx_width   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
     const int        idx_height  = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
     const int        idx_batch   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);

     // Create kernel
     CLBuildOptions build_opts;
     build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
     build_opts.add_option("-DWIDTH_OUT=" + support::cpp11::to_string(output->info()->dimension(idx_width)));
     build_opts.add_option("-DHEIGHT_OUT=" + support::cpp11::to_string(output->info()->dimension(idx_height)));
     build_opts.add_option("-DBATCH_SIZE=" + support::cpp11::to_string(output->info()->dimension(idx_batch)));
     build_opts.add_option("-DWIDTH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_width)));
     build_opts.add_option("-DHEIGHT_IN=" + support::cpp11::to_string(input->info()->dimension(idx_height)));
     build_opts.add_option("-DBATCH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_batch)));
     build_opts.add_option("-DBLOCK_SHAPE_X=" + support::cpp11::to_string(block_shape_x));
     build_opts.add_option("-DBLOCK_SHAPE_Y=" + support::cpp11::to_string(block_shape_y));
     build_opts.add_option("-DPAD_LEFT_X=" + support::cpp11::to_string(padding_left.x()));
     build_opts.add_option("-DPAD_RIGHT_X=" + support::cpp11::to_string(padding_right.x()));
     build_opts.add_option("-DPAD_LEFT_Y=" + support::cpp11::to_string(padding_left.y()));
     build_opts.add_option("-DPAD_RIGHT_Y=" + support::cpp11::to_string(padding_right.y()));
     _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("space_to_batch_static_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options()));

     // Configure kernel window
     Window win = calculate_max_window(*output->info(), Steps());
     ICLKernel::configure_internal(win);
 }

 Status CLSpaceToBatchLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *block_shape, const ITensorInfo *paddings, const ITensorInfo *output)
 {
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, block_shape, paddings, output));
     return Status{};
 }
 Status CLSpaceToBatchLayerKernel::validate(const ITensorInfo *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right,
                                            const ITensorInfo *output)
 {
     ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_static(input, block_shape_x, block_shape_y, padding_left, padding_right, output));
     return Status{};
 }

 void CLSpaceToBatchLayerKernel::run(const Window &window, cl::CommandQueue &queue)
 {
     ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
     ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);

     Window slice_out = window.first_slice_window_3D();

     Window slice_in = window.first_slice_window_4D();
     slice_in.set(Window::DimX, Window::Dimension(0, 0, 0));
     slice_in.set(Window::DimY, Window::Dimension(0, 0, 0));
     slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0));
     slice_in.set(3, Window::Dimension(0, 0, 0));

     Window vector_slice = window.first_slice_window_1D();
     vector_slice.set(Window::DimX, Window::Dimension(0, 0, 0));

     Window padding_slice = window.first_slice_window_2D();
     padding_slice.set(Window::DimX, Window::Dimension(0, 0, 0));
     padding_slice.set(Window::DimY, Window::Dimension(0, 0, 0));

     int batch_id = 0;
     do
     {
         unsigned int idx  = 0;
         const bool   cond = (_paddings != nullptr && _block_shape != nullptr);
         add_4D_tensor_argument(idx, _input, slice_in);
         add_2D_tensor_argument_if(cond, idx, _paddings, padding_slice);
         add_1D_tensor_argument_if(cond, idx, _block_shape, vector_slice);

         add_argument(idx, batch_id);
         add_3D_tensor_argument(idx, _output, slice_out);
         enqueue(queue, *this, slice_out);
         ++batch_id;
     }
     while(window.slide_window_slice_3D(slice_out));
 }
 } // namespace arm_compute
	/*
	* Copyright (c) 2018-2019 ARM Limited.
	*
	* SPDX-License-Identifier: MIT
	*
	* Permission is hereby granted, free of charge, to any person obtaining a copy
	* of this software and associated documentation files (the "Software"), to
	* deal in the Software without restriction, including without limitation the
	* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
	* sell copies of the Software, and to permit persons to whom the Software is
	* furnished to do so, subject to the following conditions:
	*
	* The above copyright notice and this permission notice shall be included in all
	* copies or substantial portions of the Software.
	*
	* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
	* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
	* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
	* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
	* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
	* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
	* SOFTWARE.
	*/
	#include "arm_compute/core/CL/kernels/CLSpaceToBatchLayerKernel.h"

	#include "arm_compute/core/CL/CLHelpers.h"
	#include "arm_compute/core/CL/CLValidate.h"
	#include "arm_compute/core/CL/ICLTensor.h"
	#include "arm_compute/core/utils/misc/ShapeCalculator.h"

	using namespace arm_compute::misc::shape_calculator;

	namespace arm_compute
	{
	namespace
	{
	Status validate_arguments(const ITensorInfo input, const ITensorInfo block_info, const ITensorInfo padddings, const ITensorInfo output)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, block_info, padddings, output);
	ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(block_info, 1, DataType::S32);
	ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);
	ARM_COMPUTE_RETURN_ERROR_ON(block_info->num_dimensions() > 1);
	ARM_COMPUTE_RETURN_ERROR_ON(padddings->num_dimensions() > 2);
	ARM_COMPUTE_RETURN_ERROR_ON(padddings->tensor_shape()[1] != block_info->tensor_shape()[0]);

	// Validate output if initialized
	if(output->total_size() != 0)
	{
	const DataLayout data_layout = input->data_layout();
	const int idx_channel = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
	ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_channel] != output->tensor_shape()[idx_channel]);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
	}

	return Status{};
	}
	Status validate_arguments_static(const ITensorInfo *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right,
	const ITensorInfo *output)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
	ARM_COMPUTE_RETURN_ERROR_ON(block_shape_x < 1 \|\| block_shape_y < 1);
	ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4);

	// Validate output if initialized
	if(output->total_size() != 0)
	{
	const DataLayout data_layout = input->data_layout();
	const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
	const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
	const int idx_channel = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
	const int idx_batch = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);
	ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_width] < padding_left.x() + padding_right.y());
	ARM_COMPUTE_RETURN_ERROR_ON((input->tensor_shape()[idx_width] + padding_left.x() + padding_right.x()) % block_shape_x != 0);
	ARM_COMPUTE_RETURN_ERROR_ON((input->tensor_shape()[idx_height] + padding_left.y() + padding_right.y()) % block_shape_y != 0);
	ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_channel] != output->tensor_shape()[idx_channel]);
	ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_batch] % (block_shape_x * block_shape_y) != 0);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
	}

	return Status{};
	}
	} // namespace

	CLSpaceToBatchLayerKernel::CLSpaceToBatchLayerKernel()
	: _input(nullptr), _block_shape(nullptr), _paddings(nullptr), _output(nullptr)
	{
	}

	void CLSpaceToBatchLayerKernel::configure(const ICLTensor input, const ICLTensor block_shape, const ICLTensor paddings, ICLTensor output)
	{
	ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
	ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), block_shape->info(), paddings->info(), output->info()));

	_input = input;
	_block_shape = block_shape;
	_paddings = paddings;
	_output = output;

	const DataLayout data_layout = input->info()->data_layout();
	const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
	const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
	const int idx_batch = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);

	// Create kernel
	CLBuildOptions build_opts;
	build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
	build_opts.add_option("-DWIDTH_OUT=" + support::cpp11::to_string(output->info()->dimension(idx_width)));
	build_opts.add_option("-DHEIGHT_OUT=" + support::cpp11::to_string(output->info()->dimension(idx_height)));
	build_opts.add_option("-DBATCH_SIZE=" + support::cpp11::to_string(output->info()->dimension(idx_batch)));
	build_opts.add_option("-DWIDTH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_width)));
	build_opts.add_option("-DHEIGHT_IN=" + support::cpp11::to_string(input->info()->dimension(idx_height)));
	build_opts.add_option("-DBATCH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_batch)));
	_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("space_to_batch_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options()));

	// Configure kernel window
	Window win = calculate_max_window(*output->info(), Steps());
	ICLKernel::configure_internal(win);
	}

	void CLSpaceToBatchLayerKernel::configure(const ICLTensor *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right,
	ICLTensor *output)
	{
	ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);

	TensorShape output_shape = misc::shape_calculator::compute_space_to_batch_shape(input->info(), block_shape_x, block_shape_y, padding_left, padding_right);
	auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->quantization_info());

	ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_static(input->info(), block_shape_x, block_shape_y, padding_left, padding_right, output->info()));

	_input = input;
	_output = output;

	const DataLayout data_layout = input->info()->data_layout();
	const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
	const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
	const int idx_batch = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES);

	// Create kernel
	CLBuildOptions build_opts;
	build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
	build_opts.add_option("-DWIDTH_OUT=" + support::cpp11::to_string(output->info()->dimension(idx_width)));
	build_opts.add_option("-DHEIGHT_OUT=" + support::cpp11::to_string(output->info()->dimension(idx_height)));
	build_opts.add_option("-DBATCH_SIZE=" + support::cpp11::to_string(output->info()->dimension(idx_batch)));
	build_opts.add_option("-DWIDTH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_width)));
	build_opts.add_option("-DHEIGHT_IN=" + support::cpp11::to_string(input->info()->dimension(idx_height)));
	build_opts.add_option("-DBATCH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_batch)));
	build_opts.add_option("-DBLOCK_SHAPE_X=" + support::cpp11::to_string(block_shape_x));
	build_opts.add_option("-DBLOCK_SHAPE_Y=" + support::cpp11::to_string(block_shape_y));
	build_opts.add_option("-DPAD_LEFT_X=" + support::cpp11::to_string(padding_left.x()));
	build_opts.add_option("-DPAD_RIGHT_X=" + support::cpp11::to_string(padding_right.x()));
	build_opts.add_option("-DPAD_LEFT_Y=" + support::cpp11::to_string(padding_left.y()));
	build_opts.add_option("-DPAD_RIGHT_Y=" + support::cpp11::to_string(padding_right.y()));
	_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("space_to_batch_static_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options()));

	// Configure kernel window
	Window win = calculate_max_window(*output->info(), Steps());
	ICLKernel::configure_internal(win);
	}

	Status CLSpaceToBatchLayerKernel::validate(const ITensorInfo input, const ITensorInfo block_shape, const ITensorInfo paddings, const ITensorInfo output)
	{
	ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, block_shape, paddings, output));
	return Status{};
	}
	Status CLSpaceToBatchLayerKernel::validate(const ITensorInfo *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right,
	const ITensorInfo *output)
	{
	ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_static(input, block_shape_x, block_shape_y, padding_left, padding_right, output));
	return Status{};
	}

	void CLSpaceToBatchLayerKernel::run(const Window &window, cl::CommandQueue &queue)
	{
	ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
	ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);

	Window slice_out = window.first_slice_window_3D();

	Window slice_in = window.first_slice_window_4D();
	slice_in.set(Window::DimX, Window::Dimension(0, 0, 0));
	slice_in.set(Window::DimY, Window::Dimension(0, 0, 0));
	slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0));
	slice_in.set(3, Window::Dimension(0, 0, 0));

	Window vector_slice = window.first_slice_window_1D();
	vector_slice.set(Window::DimX, Window::Dimension(0, 0, 0));

	Window padding_slice = window.first_slice_window_2D();
	padding_slice.set(Window::DimX, Window::Dimension(0, 0, 0));
	padding_slice.set(Window::DimY, Window::Dimension(0, 0, 0));

	int batch_id = 0;
	do
	{
	unsigned int idx = 0;
	const bool cond = (_paddings != nullptr && _block_shape != nullptr);
	add_4D_tensor_argument(idx, _input, slice_in);
	add_2D_tensor_argument_if(cond, idx, _paddings, padding_slice);
	add_1D_tensor_argument_if(cond, idx, _block_shape, vector_slice);

	add_argument(idx, batch_id);
	add_3D_tensor_argument(idx, _output, slice_out);
	enqueue(queue, *this, slice_out);
	++batch_id;
	}
	while(window.slide_window_slice_3D(slice_out));
	}
	} // namespace arm_compute